6 papers
SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling
Zheng Liu, Zijian He, Huiguo He +5
Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes, such as objects span differ…
AdvFD: Boosting Visual Generation via Adversarial Fr'echet Distance Loss
Mingju Gao, Jingkai Zhou, Kun Gai +2
Fréchet distance has recently emerged as an effective distribution-level objective for generator post-training, complementing the conventional sample-level diffusion and flow-match…
MetaView: Monocular Novel View Synthesis with Scale-Aware Implicit Geometry Priors
Yufei Cai, Xuesong Niu, Hao Lu +3
Current visual generation models are capable of producing high-quality content, yet they lack a coherent perception of the spatial structure. Existing generative novel view synthes…
MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training
Lianyu Pang, Tianlin Pan, Cheng Da +5
Representation alignment with pretrained vision models has recently shown strong potential for accelerating diffusion transformer training. By aligning intermediate diffusion featu…
TexEditor: Structure-Preserving Text-Driven Texture Editing
Bo Zhao, Yihang Liu, Chenfeng Zhang +3
Text-guided texture editing aims to modify object appearance while preserving the underlying geometric structure. However, our empirical analysis reveals that even SOTA editing mod…
ResTok: Learning Hierarchical Residuals in 1D Visual Tokenizers for Autoregressive Image Generation
Xu Zhang, Cheng Da, Huan Yang +3
Existing 1D visual tokenizers for autoregressive (AR) generation largely follow the design principles of language modeling, as they are built directly upon transformers whose prior…